Browsing by Author "Brian, De Beer"

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    Evaluate and design battery support services for the electrical grid
    (Stellenbosch : Stellenbosch University, 2017-12) Brian, De Beer; Rix, Arnold J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.
    ENGLISH ABSTRACT: Aside from the many existing problems on the electric network; new problems have been introduced with the increased adoption of renewable energy sources. In this thesis, how battery storage systems can be applied in order to address some of the problems is investigated. These problems include: addressing the intermittent nature of photovoltaic power plants, integrating larger photovoltaic power plant into a weak network and optimising battery storage sizing for peak load shaving. The intermittent nature of photovoltaic systems becomes a problem when there is a high penetration thereof on the electric network because the fluctuating power output is reflected in the network. Fluctuation mitigation methods, incorporating battery storage systems, are investigated and the ramp-rate control strategy is chosen for further analysis. How the strategy influences the battery storage sizing, performance and cost is analysed. To analyse the impact the ramp-rate strategy has on the performance of a battery type, a battery has to be modelled. How batteries are modelled is investigated and an energythroughput model is selected to be implemented as a tool. The tool is calibrated for two battery chemistries: a lithium (LiFePO4) and lead-acid (PbSO4) chemistry. It is found that the model favours chemistries, such as the LiFePO4 chemistry, because of its linear degrading nature. The integration of larger photovoltaic installations on a weak network is investigated. Weak networks, such as high impedance radial networks, can limit power plant installations to weak connections that can restrict the power plant installation capacity. The modelling of weak networks is investigated and one such a model is implemented in DIgSILENT PowerFactory. As a solution, control systems are created where a battery storage system can work in conjunction with an on-load tap changing transformer to prevent abnormal operating conditions during a sudden power loss. Also investigated is how the battery system should be sized in order to provide this support. It is found that batteries can strengthen the network during sudden power loss conditions. It is also found that the battery systems must be sized for high power output. The last problem that is investigated is the sizing of battery storage systems for peak load shaving. Battery storage systems are usually sized for the worst case scenario but often the worst case is an anomalous case. A statistical tool called Cook’s distance is implemented to identify outlying cases in the load profiles and remove them. The original sizing strategy is optimised and implemented in Python as a tool. Finally, the original sizing strategy is compared to optimised strategy and it is found that in most of the cases the optimised strategy can improve the energy or power requirements. Finally, the costs of each of the three problems are analysed. It is found that the battery energy storage systems required for PV output fluctuation mitigation make a substantial contribution to the levelised cost of the energy of the PV installation. The same is also found with regards to the battery energy storage system used for network strengthening; however reducing the PV installation capacity can reduce the costs considerably. For the optimised battery sizing strategy, for peak load shaving; levelised costs of energy savings of up to 24% are achieved.